Adaptive order selection with aid of genetic algorithm

Author

Ikoma, Norikazu ; Maeda, Hiroshi

Author_Institution

Dept. of Comput. Sci., Kyushu Inst. of Technol., Kitakyushu, Japan

Volume

3

fYear

1999

fDate

22-25 Aug. 1999

Firstpage

1785

Abstract

A method to estimate a nonstationary power spectrum with adaptive selection of autoregressive order is proposed. Time-varying PARCOR (partial autocorrelation coefficient) and AR (autoregressive) order are estimated from time series data. The data are assumed to be observations of vibration that contain abrupt change of spectrum due to arrivals of different signal, structural changes of vibrating object, etc. The model that consists of an autoregressive model with time-varying PARCORs and time-varying order is used. The time-varying PARCORs are estimated by a Monte Carlo filter, and the time-varying order is estimated by genetic algorithm. An application to analysis of seismic wave data is reported.

Keywords

Monte Carlo methods; autoregressive processes; filtering theory; genetic algorithms; parameter estimation; spectral analysis; time series; Monte Carlo filter; adaptive order selection; autoregressive order; nonstationary power spectrum; seismic wave data; time-varying order; time-varying partial autocorrelation coefficient; vibrating object; Computer science; Filters; Fourier transforms; Genetic algorithms; Monte Carlo methods; Power engineering and energy; Seismic waves; Spectral analysis; State estimation; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International

Conference_Location

Seoul, South Korea

ISSN

1098-7584

Print_ISBN

0-7803-5406-0

Type

conf

DOI

10.1109/FUZZY.1999.790178

Filename

790178